Resume Enhancer

Did you know that over 75% of resumes aren't seen by recruiters because they don't pass the company's computer filtering system? This project aims to fix formatting and content issues to solve that.

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Inspiration

Over 90% of Fortune 500 companies use Applicant Tracking Systems (ATS) to manage candidate applications. 75% of resumes don't even get seen by a recruiter because they fail to pass the ATS scanning due to formatting, content, or lack of keywords. As a group of students who aspire to turn into software developers or data analysts in the future, having a good resume is half of the battle in order to land the dream internship or job. Our goal was to create the perfect resume builder that would pass ATS systems and give us the best chance at landing our dream employment opportunities.

What it does

Scrapes job data from a desired field off of Indeed, filters through the keywords and compares the keywords to a user-inputted resume. It then outputs the user's information into .DOCX format for easy ATS parsing.

How we built it

  • Used Selenium web scraping to get job descriptions off of Indeed
  • Used Natural Language Toolkit and manual filtering to filter keywords in the job descriptions and the Pandas and JSON libraries to manage and analyze our dataset
  • Divided up our project into two teams, Data and Formatting, and split each team up into additional deliverable subcategories to ensure work was split evenly

Challenges we ran into

  • We did not have enough time to implement every single feature that we wanted to add, as this was already an ambitious project to get done in 24 hours, but we ended up with a working final product that we are all proud of.
  • We also had some difficulties with merging in Git, as we had multiple branches open and being edited simultaneously. Through communication and focus we were able to resolve these conflicts.
  • The resume resizing algorithm was quite difficult, but Nick solved it by manually calculating page sizes using the font weights and character sizes in Calibri, and created a dynamic resume formatter.

Accomplishments that we're proud of

  • Simply put, we ended up with a fully functional terminal application that outputs an ATS compliant resume. We accomplished all of the core functionality that we wanted, including a web scraper, data wrangler, resume formatter and resume scoring system.

What we learned

  • Once you have an idea that you are passionate about, working on it for 24 hours straight does not feel that long.
  • Nick knows more about Calibri than probably anyone else on the planet

What's next for Resume Enhancer

  • More resume templates
  • Better resizing algorithm
  • Removing and editing prior entries
  • Option to see current progress
  • Create a web application or a better UI
  • Implement PDF Parsing and PDF output
  • Implement machine learning model to implement suggestions
  • Anything that makes this project better

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